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Record W1507365251 · doi:10.4271/2000-01-sc01

The Effect of Mass, Stiffness and Geometry on Injury Outcome in Side Impacts - a Parametric Study

2000· article· en· W1507365251 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2000
Typearticle
Languageen
FieldEngineering
TopicTransportation Safety and Impact Analysis
Canadian institutionsTransport Canada
Fundersnot available
KeywordsStiffnessSide impactImpactParametric statisticsPoison controlStructural engineeringGeologyMedicineEngineeringMathematicsStatistics

Abstract

fetched live from OpenAlex

This paper reports on a cooperative research project between the Australian Department of Transport and Regional Services and Transport Canada. This project was a parametric study aimed at better understanding the effects on side impact injury risk of: * Trolley mass * Barrier stiffness * Barrier stiffness distribution * Barrier face height above ground * Crabbed or perpendicular impact * Impact Speed The following observations on injury risk can be made from the tests: * The 2 largest effects for the driver are increasing the height of the barrier face (mainly thoracic) and test speed (all body regions). * Increasing the trolley mass, with a bullet / target mass ratio less than 1, has the effect of increasing only the pubic force. * Doubling the barrier stiffness increases injury risk in only the pelvic area. * The custom high and stiff element (attempting to replicate an SUV) increases both pelvic and abdominal loading.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.926
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.257
Teacher spread0.249 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it